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Use of Big Data in Business Organizations



Research Problem and Research Questions

Literature review: Use of big data in business organisations

Theories and Models influencing big data analytics 

Importance of implementation of big data 

Factors affecting the implemented big data

Big Data acts as a competitive advantage

Ways of applying big data technologies in business




According to Khine and Shaun (2017), big data is defined as the tremendous digital data present in the business world that cannot be controlled by the normal techniques of data handling. The use of big data by business organizations is increasing rapidly as it gives better competitive advantages. Some of the organizations that are currently using big data for improved business outcomes are Google and Yahoo. The business organizations are shifting from information technology to big data as it provides better competitive outcomes, and it increases the value of organization in the market. Big data improves the competitiveness of an organization by improving its ability of decision-making.

It gives information about a variety of unused data present in the market that can be used by any organization to improves its sale, client-relationship, employee-employer relationship and competitiveness with other organizations of the business world. It gives broad information about the target audience to the organizations that, after being appropriately analysed, could be used for building marketing strategies. This literature review discusses the research problem, that is the use of big data analytics in a different business organization to build competitive advantage in detail.

It also aims at answering the research questions related to benefits or uses of big data, factors affecting it, impacts of big data and ways of applying big data in different organizations. This paper also discusses the models and theories of big data analytics used by business organizations to improve their competitiveness and value in the market.

Research Problem and Research Questions

The research problem discussed in this business research report is "Big data analytics can be used by the business organization to build competitive advantage". Big data consists of 4-Vs, velocity, veracity, volume, the variety that makes the data more complex and difficult to be handled. The process of using the analytical method to analyze these four Vs is called big data analytics. The modern computer-based technologies may lead to the successful implementation of data-based analytics in the business world. For example, NoSQL and Hadoop are the modern computer technologies that support data storage and retrieval (Liu et al. 2016).

Various business organizations have developed their software for big data, such as IBM has PureData that is based upon big data analytics. The usage of big data has increased in many sectors, such as customer management. As per (Barham 2017), the business organizations that fail to successfully implement big data technologies for evaluating their competitiveness and performance are at the risk of losing their market value in the next few years. Big data analytics improves the chances of organizations to make the right decisions at the correct period that helps in increasing the market value of organizations.

For example, the business organizations should collect the big data of their consumer feedback, evaluate it to improve their performance. This also helps in improving the competitiveness of the organizations with its competitors. Thus, big data is crucial for business organizations in improving their market value than their competitors. This literature review also aims at answering the following research questions that were mentioned in the initial research proposal:

  • What are the benefits of big data analytics technology in business?

  • Which factors are responsible for implementing the big data in business?

  • What is the impact of big data on the competitive advantage of business?

  • How firms can employ big data technology into their business?

Literature Review: Use of Big Data in Business Organisations

Theories and Models influencing big data analytics

As per Elragal and Klischewski (2018), the lightweight theory influences big data and the processes linked with significant data implementation. This aim of lightweight theory is to safeguard the information stored in the form of big data. This theory begins with the process of acquisition, that means the collection of big data from relevant sources. Preprocessing is the next step of this model that provides a background of the dataset. The step focuses on cleaning the big data to exclude it from unwanted or waste data. The next step is analytics which is also the major step of the lightweight model.

This step includes data mining, statistics and other modern techniques of data evaluation. In this step, the raw data is reconstructed to form the final data that can be used by the organizations or companies. Big data analytics can be performed by the use of support vector machines and the ensemble method. The final step is the interpretation that correlated the data obtained through analytics to existing knowledge so that the data can be used accurately in all industries. This interpreted data can be used by the organizations for decision making, improving sales, performance, enhancing market value and problem-solving. However, this is not the only model that affects or influences the big data.

The research in which the researchers only focus on the plenty of data and not upon the relevant data is called streetlight research, and this type of research has high chances of producing biased results. The accuracy of big data is also influenced by stream analysis as this type of analysis helps in analyzing the real-time data and not the pre-existing data. It handles the real-time data with a high volume by considering multiple sources of big data (Kolajo, Daramola and Adebiyi 2019). Thus, there are various theories, models and streams the influence big data and its accuracies such as lightweight theory, streaming analysis and streetlight research.

Importance of implementation of big data

Big data is highly beneficial to business organizations in today's world. It provides new opportunities to the organizations to utilize data for improving their market value (Alsghaier et al. 2017). It leads to effective operations, increases the number of satisfied customers and also provides considerable benefits to the business organizations. The data analytics tools provide development opportunities to the business organization by providing them with information about their competitors and target audience. The organizations are using information technologies to access the big data, evaluate it and then implement it to improve their decision-making skills. Google and Amazon are using the technique of big data to monitor factors that affect their performance in the market.

After this, they work to reduce the effect of these factors and improve their overall business performance. However, Facebook, as well as Twitter, are the companies that use big data analytics to examine the viewpoint of their users on their products to understand their market value. This helps them in evaluating the needs of their consumers that can help them in improving their products. Big data analytics gives opportunities to collect information about different expertise and to use them for their financial profit. It generates competitive intelligence that helps the organizations to improve their services and products by gathering information about their rivals. It also improves the efficiency, planning and management of the supply chain, which eventually improves market intelligence, market value, risk management, competitiveness, and performance of the organizations.

It enhances the mechanism of information process of the organizations that improve their decision-making skills. Although big data provides great benefits and opportunities to the business organization, it also faces various challenges. Some of these challenges are lack of accurate data resources, unavailability of enough software application to use big data analytics, data security or privacy, security regulations and many more (Ram, Zhang and Koronios 2016).

Factors affecting the implemented big data

Some of these factors include the infrastructure of information technology (IT), sources of data collection, cost, expectations of the organization and financial conditions of the organization. However, the factors that affect the process of big data collection are quality of the data, its capacity, volume, structure and culture of the organization collecting the data, data-related policies and technical software available for data collection (Wang et al. 2018). The implementation of big data is highly dependent upon the process of data collection. This is because if data collection is unsuccessful, then there are high chances that it will also be unsuccessful. The organizations must hire employees that are solely hired for collection and implementation of big data.

According to Jadega and Issa (2017), the employees that deal with big data must have specific skills for handling the large volume of this type of data. Some of these skills are statistical, logical thinking, computer or IT skill and communication skills. The volume of big data is one of the restricting factors that decrease the successful implementation, and this is the reason that organization should try to focus only the data that is useful for them and not for all the digital data available in the market. For example, if the organization belongs to the automobile industry, then it can restrict the collection of big data for automobile industry only.

It should focus on getting information about the products of its competitors within the automobile industry. It should not look for the data related to the services and products of an e-learning or healthcare industry. Other factors influencing the success of implemented big data are cost and maintenance of the applications, software and hardware that are related to big data. Thus, the factors for big data are useful for business only when they are analyzed and appropriately implemented. Identification of the key factors of big data as well as their impact on the business is very crucial for any organization.

Big Data acts as a competitive advantage

Big data has applications in various fields such as e-health, e-learning, internet of things, transportation, public sectors and government organization. In today's time, business organizations generally consider big data as a great competitive advantage to compete with their competitors. Big data has made the information more transparent and accessible. This means that the organizations can easily collect information about their rivals and can use this information for improving the quality of their products. Business organizations can produce high performance by using big data analytics. This is because big data provides information to the organizations about their customers or consumers, which can help them in evaluating the market value of their services and products.

As per Kubina, Kubinova and Varmus (2015), the market is flooding with tremendous data, but the organizations are lacking the technologies to extract the valuable data. Big data is considered as highly advantages in terms of market competition as it provides accurate information about customers, services and products. It also gives an idea about the products or services that can be highly productive in the upcoming years. The big data provides transparent data about the clients, which act as a competitive advantage. This is because the companies that are aware of their clients give better services than the ones that lack information about their target audience. It can segment the customers according to their needs which eventually helps the company to provide services according to the segmented customers. For example, few customers like to drink coke while others like drinking Coca-Cola.

The companies can evaluate the population of customers liking Coca-Cola or coca through big data, and then they can maintain the production of these drinks according to the collected data. This will help the companies in giving a better performance than their competitors and will increase their overall market value. As per Ajah and Nweke (2019), the use of big data is now used in various sectors such as healthcare, education industries, financial industries, energy consumption industries and many more. Thus, big data can help the business organization to achieve their revenues and to gain higher positions in the industry.

Ways of applying big data technologies in business

Technology that is based on the collection of big data is called big data technology or BDT. The development of BDT is important because traditional data handling methods cannot control the volume of big data (Oussous et al. 2018). This is the reason that the demand of BDT and big data applications have increased in the last few years. The business organizations have developed various types of software, programs, hardware and techniques to store their data for an extended time as it ensures to provide secure and correct big data. The organizations can adopt DBT by using significant data machine learning as it recommends the search engines and data mining applications through which big data is accessed and used.

Another method that can help organizations in adopting big data technologies is data mining methods. It helps the organization to extract only the valuable data out of the huge volume of big data. The use of modern machine-learning can help in the extraction of data and the process of information retrieval. The business organization can merge modern information technologies with big data analytics for the successful implementation of big data. Hadoop technology is a type of BDT that is commonly used by different organizations to reduce the complexity of the collected big data. It helps in the evaluation of the big data and improves its accuracy to improve the organization's performance.

As per Khine and Shoun (2017), the big data technologies can be applied in organizations in three steps. The first step is planning that includes building strategies with business objectives. Next, is the implementation in which the data is collected, cleaned by the methods of data cleaning, integrated, transformed, analyzed and represented. The final or the last step is post-implementation that includes evaluation of the outcomes of implemented big data. The organizations are currently following these three steps; planning, implementation and post-implementation to employee DBT in their business. Thus, these are some of the common ways adopted by the business organization for the implementation of big data.


Thus, this literature review concludes that big data is important for all business organizations as it increases their performance, competitiveness and market value. It is helpful in a variety of industries, such as e-commerce and healthcare. The big data helps the organizations to get feedbacks and client reviews about their products and services. It is influenced by lightweight theory, stream analysis and streetlight resources. This review also provides certain answers to the research questions such as it provides information about the impacts of big data, the importance of big data and DBT in the business world. The ways that can be used by different organizations to use DBT and implement big data are also discussed in this report. It also discusses the ways in which big data, DBT and big data analytics can be used as a competitive advantage by organizations.

For example, the organizations can collect information about the views of customers or clients on their products or services, and they can obtain this information in improving their products and services. This will improve their position and will help them in becoming leading organizations by successfully competing with their rivals. Moreover, it also discusses some of the big data technologies or DBT that organizations can use for implementing or applying big data. However, the gap present in this report is the absence of challenges that organizations have to face while implementing big data. It also lacks the negative impacts of DBT and big data on the business organizations and cooperative world.


Ajah, A. I. and Nweke, F. H. 2019. Big data and business analytics: trends, platforms, success factors and applications. MDPI, 3(2) pp. 2-32. https://doi.org/10.3390/bdcc3020032

Alsghaier, H., Akour, M., Shehabat, I. and Aldiabat, A. 2017. The importance of big data analytics in business: a case study. American Journal of Software Engineering and Applications, 6(4), pp. 111-115. https://doi.org/10.11648/j.ajsea.20170604.12

Barham, H. 2017. Achieving competitive advantage through big data: A literature review. PICMET. https://doi.org/10.23919/PICMET.2017.8125459

Elragal, A. and Klischewski, R. 2017. Theory-driven or process-driven prediction? Epistemological challenges of big data analytics. Journal of Big Data, 4(1), pp. n.d. https://doi.org/10.1186/s40537-017-0079-2

Jadega, B. and Issa, T. 2018. Big Data-A new technology trend and factors affecting the implementation of big data in Australian industries. Springer, 10(n.d.), pp. 259-287.https://doi.org/10.1007/978-3-319-67925-911

Khine, P. V. and Shun, Z. W. 2017. Big data for organizations: A review. Journals of Computer and Communication, 5(3). https://doi.org/10.4236/jcc.2017.53005

Kolajo, T., Daramola, O. and Adebiyi, A. 2019. Big data stream analysis: a systematic literature review. Journal of Big Data, 6(47), pp. 1-30. https://doi.org/10.1186/s40537-019-0210-7

Kubina, M., Varmus, M. and Kubinova, I. 2015. Use of big data for competitive advantage of company. Procedia Economics and Finance, 26(n.d.), pp. 561-565. https://doi.org/10.1016/S2212-5671(15)00955-7

Liu, O., Chong, W. K. and Chan, O. C. 2016. The application of big data analytics in business world. IMCES, 2(n.d.), pp. 16-18. http://www.iaeng.org/publication/IMECS2016/IMECS2016_pp665-667.pdf

Oussous, A., Benjelloun, Z. F., Lahcen, A. A. and Belfkih, S. 2018. Big data technologies: A survey. Journal of King Saud University - Computer and Information Sciences, 30(4), pp. 441-448. https://doi.org/10.1016/j.jksuci.2017.06.001

Ram, J., Zhang, C. and Koronios, A. 2016. The implications of Big Data analytics on Business Intelligence: A qualitative study in China. Procedia Computer Science, 87(n.d.), pp. 221-226. https://doi.org/10.1016/j.procs.2016.05.152

Wang, L., Yang, M., Pathan, H. Z., Salam, S., Shazad, K. and Zeng, J. 2018. Analysis of influencing factors of big data adoption in Chinese enterprises using DANP technique. MDPI, 10(11), pp. 1-16. https://doi.org/10.3390/su10113956

Remember, at the center of any academic work, lies clarity and evidence. Should you need further assistance, do look up to our Business Research Assignment Help

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